Abstract:
Mobile computing is increasingly attracting attention of researchers to
revisit the conventional implementation of distributed computing paradigms
for use in this new environment. In this paper we propose to revisit the
conventional implementation of the Two Phase Commit (2PC) protocol which
is a fundamental asset of transactional technology for ensuring consistent
effects of distributed transactions. We propose a new execution framework
to provide an efficient extension that is aware of the mobility of the
mobile host. The proposed M-2PC (Mobility-aware 2PC protocol preserves the
2PC principle and the freedom of the mobile clients and servers while it
minimizes the impact of wireless and unreliable.

Abstract:In this paper we propose
a new algorithm for image registration which is a key stage in almost
every computer vision system. The algorithm is inspired from both genetic
algorithms and quantum computing fields and uses the mutual information as
a measure of similarity. The proposed approach is based on some concepts
and principles of quantum computing such as quantum bit and states
superposition. So, the definitions of the basic genetic operations have
been adapted to use the new concepts. The evaluation of each solution is
performed by the computation of mutual information between the reference
image and the resulting image. The process aims to maximize this mutual
information in order to get the best affine transformation parameters
which allow the alignment of the two images.

Abstract:This
paper introduces a new algorithm to reduce the time of updating the
weights of auto-association multilayer perceptrons network. The basic idea
is to modify the singular value decomposition which has been used in the
batch algorithm to update the weights whenever a new row is added to the
input matrix. The computation analysis and the experiments show that the
new algorithm speeds up the implementation about 5-8 times.

Abstract:
The
world of computing is moving towards a trend where tasks are being done in
a distributed manner. This is especially relevant in distributed
transaction processing systems used by financial institutions, where a
single transaction could result in significant changes in other parts of
the system. In a distributed system, a transaction often involves the
participation of multiple sites and access of shared data in remote
locations. A failure of one site in committing its part of the transaction
could cause the entire system to be inconsistent. Thus, some form of
control is necessary to ensure that concurrent execution of transactions
in a distributed environment does not jeopardize the integrity of the
system as well as its data consistency. In this work a Two-Phase Commit
Protocol (2PC) simulator was developed using Java Remote Method Invocation
(RMI) in order to visualize and monitor the execution of transactions and
their failure and recovery.

Abstract:
Recently data communication spread to the mobile wireless world. The
complexity of medium and large speech & speaker recognition systems are
beyond the memory and computational resources of the small portable
devices. Moreover the most common approach to speaker recognition today is
the use of global Gaussian mixture models (GMM) which ignores knowledge of
the underlying phonetic content of the speech, so it does not take
advantage of all available information. In this paper we address the
solution of these two problems by investigating the phoneme effect on
speaker recognition system. We used YOHO database for speaker
identification task. We found that some phonemes have strong effect on
speaker identification. Segmenting the most effective phoneme for speaker
recognition task from a speaker utterance and send this phoneme only
through the wireless communication system will decrease the complexity of
medium and speed up the authentication process though mobile communication
system. We have applied different approaches on YOHO corpus, several of
these approaches were able outperform previously published results on the
speaker ID task. One of our approaches could achieve 0.7% error rate by
using only an average segment of 4.45% of the testing utterance for
recognition.

Abstract:This paper presents a
new algorithm that simplifies the process of generating and expanding
cipher key, which is considered one of the most important elements in
ciphering process. This algorithm generates a pool of keys, and then sends
this pool to the authorized receiver. Sender will use this pool to select
the schedule key randomly. In key exchange, receiver will get the index of
the first element in the schedule key at the other and the algorithm
extracts the schedule key and uses it to decipher the ciphered block
without key re-expansion.

Abstract:Classical
genetic algorithms (CGA) are known to find good sub-optimal solutions for
complex and intractable optimization problems. In many cases, problems
undergo frequent minor modifications, each producing a new problem
version. If these problems are not small in size, it becomes costly to use
a genetic algorithm to reoptimize them after each modification. In this
paper, we propose an Incremental Genetic Algorithm (IGA) to reduce the
time needed to reoptimize modified problems.The idea of IGA is simple and
leads to useful results. IGA is similar to CGA except that it starts with
an initial population that contains chromosomes saved from the CGA run for
the initial problem version (prior to modifying it). These chromosomes are
best feasible and best infeasible chromosomes to which we apply two
techniques in order to ensure sufficient diversity within them. To
validate the proposed approach, we consider three problems: optimal
regression software testing, general optimization, and exam scheduling.
The empirical results obtained by applying IGA to the three optimization
problems show that IGA requires a smaller number of generations than those
of a CGA to find a solution. In addition, the quality of the solutions
produced by IGA is comparable to those of CGA.

Research
Group on Artificial Intelligence, University of Annaba, Algeria

Abstract:
This paper describes the architecture of an interactive learning
environment (ILE) on Internet using companions which one is a human and
geographically distant of the learning site. The achieved system rests on
a three-tier Customer/Server architecture (Customer, Web Server, Data and
applications Server) where human and software actors can communicate via
the Internet. and uses the DTL learning strategy. It contents five main
actors: a tutor actor in charge to guide the learner; a system actor whose
role is to manage and to control the accesses to the system; a teacher
actor in charge of the management and the updating of the different bases;
a llearner actor who represents the main actor of the system for whom is
dedicated the teaching. And a learning companion actor whose role can be
sometimes as an assistant, and other times, as a troublemaker.

Abstract:The paper explains a
framework that has been proposed to construct a dynamic delivery tree for
the mobile node (MN) movement in a mobile IPv6 network. The branches of
the tree constitute the shortest paths from the packet source to each of
the visited locations. The tree is dynamic such that the branches grow and
shrink to reach the MN when necessary. This architecture is
multicast-based, in which a mobile node is assigned a multicast address
and the correspondent nodes send packets to that multicast group. As the
mobile node moves to a new location, it joins the multicast group through
the new location and prunes through the old location. Hash Algorithm has
been implemented as a mechanism for the MN to join and leave a multicast
group. Dynamics of the multicast tree provide for smooth handoff,
efficient routing and conservation of network bandwidth. To allow a smooth
handoff, the MN should not prune the old location until it starts
receiving packets from the new location. The performance of the proposed
mechanism was evaluated through a simulation model built for this purpose.
The simulation results showed that the dynamics of joining and leaving the
group directly affect handoff latency and smoothness, as a result it
conserved radio frequency (RF) bandwidth.

3Dept. of
Information and Computer Science, King Fahd University of Petroleum and
Minerals, SA

Abstract:
MOSIX (Multicomputer Operating System for Unix) is a cluster-computing
enhancement of Linux kernel that supports preemptive process migration. It
consists of adaptive resource sharing algorithms for high performance
scalability by migrating processes across a cluster. MPI (Message Passing
Interface) is a library standard for writing message passing programs,
which has the advantage of portability and ease of use. This paper
highlights the advantages of a process migration model to utilize
computing resources better and gain considerable speedups in the execution
of parallel and multi-tasking applications. We executed several CPU bound
tests under MPI and MOSIX. The results of these tests show the advantage
of using MOSIX over MPI. At the end of this paper, we present the
performance of the executions of those tests, which showed that in some
cases improvement in the performance of MOSIX over MPI can reach tens of
percents.

Abstract:
The
main idea in this paper is to detect regions(objects) and their
boundaries, also to isolate and extract individual components from a
medical image. This can be done using K-means firstly to detect regions in
a given image. Then based on techniques of curve evolution, Chan-Vese for
segmentation and level sets approaches to detect the edges around each
selected region. Once we classified our images into different intensity
regions based on K-means method, to be easy to separate each region with
its boundary and its area individually in the next steps . Then we detect
regions whose boundaries are not necessarily defined by gradient using
Chan-Vese algorithm for segmentation. In the level set formulation, the
problem becomes a mean-curvature flow like evolving the active contour,
which will stop on the desired boundary of our selected region results
from K- means step. The final image segmentation results are one closed
boundary per actual region in the image and segmented map

Abstract:
Higher education based on the Information Technology is found to be a
feasible and economical model in improving the traditional education model
[1, 2]. Consequently e-Learning portals have been used to design online
courses according to the course goals and students needs. A basic goal of
on-line course design is to provide almost a complete course environment
including a virtual lab related to each course if needed. This allows
students to access the entire course environment in on-line at anytime,
and from anywhere. This paper explains the development of a feasible
system architecture that extends the services of a portal by integrating
software tools as part of the designed on-line courses. The resulting
architecture is simple, distributed resources and cost effective. The
supporting experimental work has been carried out on the test bed around
the e-Learning portal WebCT that is currently available in SQU (Sultan
Qaboos University).

Abstract:
According to Voas et al. testability is defined as the ease with which
faults may manifest themselves as failures when the software undergoes the
testing process [1]. They also went further by introducing an approach for
measuring sensitivity in terms of estimates from Propagation, Infection
and Execution (PIE) analyses of software and calculating the testability
of a program through sensitivity estimate. Their testability calculations
‘by hand’ to determine the stability of the PIE analysis technique had
drawbacks such as more time-consuming, high cost and less precision in the
overall results [2]. Particularly the infection analysis part is one of
the most expensive, sophisticated and time-consuming component of the PIE
analysis technique. In order to solve this problem an investigation has
been carried out by the author for establishing the feasibility of
automating (or partially automating) the PIE analysis technique by means
of a fast, and computationally less expensive approach [3]. A Mutant
Schemata Generation Infection (MSG-Infection) tool has been developed to
automate PIE analyses partially. This paper introduces the MSG-Infection
tool briefly and explains the method of automating the PIE analyses
technique. It also presents the results indicating a significant
improvement in performance due to MSG-Infection tool.